Monitoring and quality assessment of urban development areas based on neural network modeling and GIS
In this article the authors carry out the research of the urban development areas structure and propose the system of its characteristics on the basis of sector affiliation of the municipal economy. The authors have developed an algorithm for quality assessment of urban development areas. The results of the research are presented on the example of several central city quarters of Arkhangelsk. Structural SOM-analysis compiled separate quarters of Arkhangelsk into 5 groups with a high level of characteristic similarity: "Commercial", "Prospective complex development", "Sustainable development", "Perspective renovation of residential development", "Investment-unattractive". Typical development strategies for each group of quarters are determined. Using GIS allows to visually reflect the state and assess the quality of the urban development area by the aggregate of all parameters, and also to assess the quality of the quarters for each sector. The proposed method is universal. It makes it possible to vary the list and the set of characteristics; to apply the method for monitoring and assessment of different areas, regardless of their geolocation and scale; to adapt the methodology for monitoring other processes occurring in urban areas. "Fast" algorithm processing allows one to accelerate the planning and adjust the programs of urban areas reproduction in real time, reduce the expenses of time and resources on monitoring and analyzing data. The proposed methodology can be used as a mechanism for the formation of a long-term town-planning strategy for the urban development area along with the planning of reproductive activities taking into account their investment and social efficiency.